{"id":"W4284882048","doi":"10.1097/cin.0000000000000940","title":"The Psychometric Properties of Version 2 of the Canadian Nurse Informatics Competency Assessment Scale","year":2022,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Nursing Diagnosis and Documentation","field":"Nursing","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton; University of New Brunswick","funders":"","keywords":"Varimax rotation; Health informatics; Informatics; Scale (ratio); Exploratory factor analysis; Nursing; Reliability (semiconductor); Psychology; Medical education; Medicine; Psychometrics; Cronbach's alpha; Clinical psychology; Public health; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.000667715,0.0001662961,0.0002472258,0.0004154957,0.001810058,0.0001446028,0.000704916,0.0000473207,0.00001232451],"category_scores_gemma":[0.00003296262,0.0001166279,0.0001400019,0.001101152,0.0003456827,0.0003515796,0.00007037928,0.0003410959,0.000002675332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092431,"about_ca_system_score_gemma":0.0002774466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001444431,"about_ca_topic_score_gemma":0.0005035239,"domain_scores_codex":[0.9975607,0.0001459619,0.001001016,0.00007191348,0.0008617964,0.0003585772],"domain_scores_gemma":[0.9982823,0.0001531498,0.0007879243,0.0005013227,0.0001778605,0.00009751581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003973423,0.00107974,0.04550775,0.001100375,0.000190278,4.975576e-7,0.2114047,0.07796587,0.0008665799,0.005330757,0.1341015,0.5220546],"study_design_scores_gemma":[0.005782761,0.002363726,0.1131401,0.00519486,0.0005191021,0.000104508,0.1775171,0.6198376,0.0219809,0.002799169,0.04946185,0.001298302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968789,0.0003510061,0.001796879,0.005059752,0.01157729,0.001246592,0.00003442496,0.00005293043,0.01109207],"genre_scores_gemma":[0.993078,0.000008083617,0.006280264,0.0005398779,0.00003220052,0.00001506509,0.00001765627,0.00001506852,0.00001380826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5418717,"threshold_uncertainty_score":0.9994894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204645129229247,"score_gpt":0.2664609175608862,"score_spread":0.2544144662685938,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}